code: def test_zeropadding(
      keras_model_1d,
      keras_model_2d,
      data_1d,
      data_2d,
      model_type,
      io_type,
      backend,
  ):
      if model_type == "1d":
          model = keras_model_1d
          data = data_1d
      else:
          model = keras_model_2d
          data = data_2d
  
      config = hls4ml.utils.config_from_keras_model(
          model, default_precision="ap_fixed<32,1>", granularity="name"
      )
      odir = str(
          test_root_path
          / f"hls4mlprj_zeropadding_{model_type}_{backend}_{io_type}"
      )
      hls_model = hls4ml.converters.convert_from_keras_model(
          model,
          hls_config=config,
          io_type=io_type,
          output_dir=odir,
          backend=backend,
      )
      hls_model.compile()
  
      # Predict
      y_keras = model.predict(data).flatten()
      y_hls = hls_model.predict(data).flatten()
      np.testing.assert_allclose(
          y_keras, y_hls, rtol=0, atol=atol, verbose=True
      )
  
file_path: hls4ml/test/pytest/test_zeropadding.py
imports: from pathlib import Path
  import numpy
  import pytest
  from tensorflow.keras.layers import ZeroPadding1D, ZeroPadding2D
  from tensorflow.keras.models import Sequential
  import hls4ml
label_desc: Use image node_id 5 for calling a global function with example usage: test_zeropadding(keras_model_1d, keras_model_2d, data_1d, data_2d, model_type, io_type, backend) without return types